A Modular Robot Transplantation Method Based on the Improved Inverse Distance Weighting Method Proxy Model

Abstract

When integrating evolutionary algorithms into the process of the design of modular robots, the "reality gap" problem leads to the difference between simulation and reality. A modular robot transplantation method based on the improved inverse distance weighting method proxy model is presented. Based on the plane moving task, the portability of the modular robot consisting of EMERGE modules of different shapes and types was experimentally studied. The information of other real robots can be predicted according to the limited evolutionary data of real robots. It is no need to do all the evaluation experiments on a physical robot. The number and complexity of experiments are reduced. the experiment efficiency is improved. This method can effectively reduce the performance difference between the results of simulation and the real robot caused by the "reality gap" problem, and the portability of modular robots improves greatly.